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IQ.Pilot Release Commit @ f2a861c

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IQ.Lvbs CI [bot]
2026-09-02 15:07:09 -05:00
parent b42569dbca
commit e8748fd704
5497 changed files with 316070 additions and 179848 deletions
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17
iqpilot/selfdrive/iqmodeld/tools/compile_supercombo.py
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@@ -59,7 +59,6 @@ def warp_perspective_tinygrad(src_flat, M_inv, dst_shape, src_shape, stride_pad,
x = Tensor.arange(w_dst).reshape(1, w_dst).expand(h_dst, w_dst).reshape(-1)
y = Tensor.arange(h_dst).reshape(h_dst, 1).expand(h_dst, w_dst).reshape(-1)
# inline 3x3 matmul as elementwise to avoid reduce op (enables fusion with gather)
src_x = M_inv[0, 0] * x + M_inv[0, 1] * y + M_inv[0, 2]
src_y = M_inv[1, 0] * x + M_inv[1, 1] * y + M_inv[1, 2]
src_w = M_inv[2, 0] * x + M_inv[2, 1] * y + M_inv[2, 2]
@@ -100,9 +99,7 @@ def make_frame_prepare(nv12: NV12Frame, model_w, model_h):
stride_pad = stride - cam_w
def frame_prepare_tinygrad(input_frame, M_inv):
# UV_SCALE @ M_inv @ UV_SCALE_INV simplifies to elementwise scaling
M_inv_uv = M_inv * Tensor([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]], device=WARP_DEV)
# deinterleave NV12 UV plane (UVUV... -> separate U, V)
uv = input_frame[uv_offset:uv_offset + uv_height * stride].reshape(uv_height, stride)
with Context(SPLIT_REDUCEOP=0):
y = warp_perspective_tinygrad(input_frame[:cam_h*stride],
@@ -142,7 +139,6 @@ def get_policy_npy_shapes(input_shapes):
tc = input_shapes['traffic_convention'] # (1, 2)
at = input_shapes['action_t'] # (1, 2)
fb = input_shapes['features_buffer'] # (1, 24, 512)
# TODO prev_feat shouldn't exist and be handled inside the JIT, but corrupt on QCOM for now
shapes = {'desire': (dp[2],), 'traffic_convention': tuple(tc), 'action_t': tuple(at), 'prev_feat': (fb[0], fb[2])}
return shapes, [math.prod(s) for s in shapes.values()]
@@ -155,7 +151,6 @@ def make_input_queues(input_shapes, frame_skip, device):
shapes, sizes = get_policy_npy_shapes(input_shapes)
packed_npy_inputs = np.zeros(sum(sizes), dtype=np.float32)
# views into the packed inputs, to be refilled at runtime
npy.update({k: v.reshape(s) for (k, s), v in zip(shapes.items(), np.split(packed_npy_inputs, np.cumsum(sizes[:-1])), strict=True)})
input_queues.update({
'feat_q': Tensor(np.zeros((frame_skip * fb[1], fb[0], fb[2]), dtype=np.float32), device=device).contiguous().realize(),
@@ -284,7 +279,7 @@ def _slice_outputs(model_outputs: np.ndarray, output_slices: dict[str, slice]) -
def _validate_pose_outputs(parsed_outputs: dict[str, np.ndarray]) -> None:
from openpilot.selfdrive.locationd.locationd import MIN_STD_SANITY_CHECK, ROTATION_SANITY_CHECK, TRANS_SANITY_CHECK
from iqpilot.selfdrive.locationd.locationd import MIN_STD_SANITY_CHECK, ROTATION_SANITY_CHECK, TRANS_SANITY_CHECK
required = (
'pose', 'pose_stds', 'wide_from_device_euler', 'wide_from_device_euler_stds',
@@ -326,7 +321,7 @@ def _validate_pose_outputs(parsed_outputs: dict[str, np.ndarray]) -> None:
def validate_supercombo_release(run_policy_jit, model_runner, model_metadata, frame_skip, expected_device: str) -> None:
from openpilot.iqpilot.selfdrive.iqmodeld.parser import PhaseParser
from iqpilot.selfdrive.iqmodeld.parser import PhaseParser
direct_fn = make_run_policy(model_runner, model_metadata, frame_skip)
parser = PhaseParser()
@@ -370,8 +365,8 @@ def _parse_size(s):
def read_file_chunked_to_shm(path):
from openpilot.common.file_chunker import read_file_chunked
from openpilot.system.hardware.hw import Paths
from iqpilot.common.file_chunker import read_file_chunked
from iqpilot.system.hardware.hw import Paths
with tempfile.NamedTemporaryFile(prefix='compile_modeld_', dir=Paths.shm_path(), delete=False) as f:
f.write(read_file_chunked(path))
tmp_path = f.name
@@ -381,8 +376,8 @@ def read_file_chunked_to_shm(path):
if __name__ == "__main__":
from tinygrad.nn.onnx import OnnxRunner
from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
from openpilot.iqpilot.selfdrive.iqmodeld.metadata import build_metadata_record
from iqpilot.system.camerad.cameras.nv12_info import get_nv12_info
from iqpilot.selfdrive.iqmodeld.metadata import build_metadata_record
p = argparse.ArgumentParser()
p.add_argument('--model-size', type=_parse_size, required=True, help='model input WxH')
p.add_argument('--camera-resolutions', type=_parse_size, nargs='+', required=True,